Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
Deterministic, non-generative image transform MCP server: reproducible recipes, immutable originals.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"atx": {
"command": "npx",
"args": [
"-y",
"atx-mcp",
"--workspace",
"your-value"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add atx -- npx -y atx-mcp --workspace your-valueEste necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"atx": {
"command": "npx",
"args": [
"-y",
"atx-mcp",
"--workspace",
"your-value"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"atx": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"atx-mcp",
"--workspace",
"your-value"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub gridhra, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.6.7) llegó al registro hace 11 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Rust, Docker, Node.js en tu computadora.
En la misma categoría: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
English | 日本語 | 简体中文
A deterministic (non-generative) asset transformation MCP server for general-purpose AI agents, written in Rust.
It executes editing intent — "level the horizon, crop to 16:9, brighten it up a touch" — as a declarative transform recipe, and tracks every result as an immutable revision. The original asset is never modified.
Tilt correction + auto levels + a look applied (a fully deterministic recipe) — left: input / right: output.
See docs/DESIGN.md for the full design.
"Straighten this photo and crop it to a 16:9, 1600px eye-catch. WebP."
import_asset → detect_tilt (the AI skips correction when it's already near-level) → apply_transform (rotate → crop → resize → encode) → export_asset. The original is never touched, and the same recipe reproduces the same result every time.
"Generate the OGP, Instagram square, and thumbnail versions of this photo."
One original fans out into OGP 1200×630, Instagram 1080 square, and a 400px thumbnail in parallel. The same-recipe-same-revision idempotency means re-running never double-creates output; a one-word preset name works too.
"Strip the location data for sure, but don't touch the colors."
strip_metadata (exif) removes EXIF including GPS while keeping the ICC profile intact. The AI can also warn ahead of time by checking has_gps from inspect_image.
"Make just the sky bluer, leave everything else alone."
Covers curves / levels / hsl / white_balance, the film_soft preset, and importing your own .cube LUT with import_asset then applying it with lut.
"Darken just the sky a bit, keep the ground as is."
generate_mask builds a mask (gradient, luminosity range, or hue range); after wiring it into the adjustment, render_preview with overlay:"mask" shows exactly where it will bite before you commit.
"Blur a copy of this photo and blend it in at 50% screen for a soft glow."
The layers stack combines 16 blend modes, opacity, and masks to build reproducible composites like soft focus.
"Stamp my logo in the corner, remove the power lines, and fix the converging verticals."
svg_overlay burns in a logo, clone/heal remove blemishes or wires by compositing both texture and tone, and perspective corrects converging verticals.
"Read this receipt photo for me." / "What does this slide say?"
detect_document finds the page or screen and returns a perspective quad ready to paste, the ocr_document preset (grayscale, auto levels, light sharpen) and trim concentrate the pixel budget on the text, and render_preview with long_edge:1568 hands the model an image it can actually read. No OCR engine is bundled: the model does the reading, atx only makes the pixels legible and reproducible. detect_text_blocks answers the question that decides the rest — "will this text survive the downscale, and where do I cut?" — by returning the text blocks in reading order plus ready-to-paste crop bands. threshold (Otsu / Sauvola) and ocr_binarize exist for external OCR engines.
"Show me this image before and after the edits, side by side."
compare_revisions places before/after side by side, or returns a difference heatmap with stats like mean_abs_diff. Every revision keeps its lineage, so the full edit history behind any image used in an article can be traced and reproduced — byte-identical on any machine.
"Two mounted sheets were scanned on one page. Save them as two files, keeping a little of the mount around each."
There is no split operation: the model runs one apply_transform per piece against the same source revision (crop to the left/right half, then trim to snap to the paper's edges with padding to keep some mount), and export_asset writes both at once. render_preview with no recipe and overlay:"grid" is how it reads the coordinates first.
What atx doesn't do — generative editing, RAW development, ML-based auto-cropping, OCR itself — is out of scope; see docs/DESIGN.md for the roadmap.
atx-mcp is a single self-contained binary with no runtime dependencies. Pick one of the following.
cargo binstall atx-mcp
claude mcp add --scope user asset-transform -- atx-mcp --workspace /path/to/asset-workspace
cargo-binstall downloads the release archive built by this repository's CI instead of compiling, so this is the fastest route for anyone who already has a Rust toolchain. (--scope user makes the server available in every project; omit it for the current project only.)
cargo install atx-mcp
Works on any platform a Rust toolchain supports, including ones without a prebuilt binary. Needs a C compiler as well (libwebp is built from its vendored source).
Installer scripts (default install location is ~/.local/bin, or %LOCALAPPDATA%\Programs\atx-mcp on Windows; the archive is verified against SHA256SUMS before extraction):
# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/gridhra/atx-mcp/main/scripts/install.sh | sh
# Windows
irm https://raw.githubusercontent.com/gridhra/atx-mcp/main/scripts/install.ps1 | iex
To download manually, grab atx-mcp- - .tar.gz (.zip on Windows) from Releases. Supported targets:
| Platform | Target triple |
|---|---|
| macOS (Apple Silicon) | aarch64-apple-darwin |
| macOS (Intel) | x86_64-apple-darwin |
| Linux x86_64 | x86_64-unknown-linux-musl (statically linked, no glibc required) |
| Linux arm64 | aarch64-unknown-linux-musl (statically linked, no glibc required) |
| Windows x86_64 | x86_64-pc-windows-msvc |
claude mcp add asset-transform -- ~/.local/bin/atx-mcp --workspace /path/to/asset-workspace
ghcr.io/gridhra/atx-mcp is a FROM scratch image holding the statically linked binary and nothing else (linux/amd64 and linux/arm64).
claude mcp add asset-transform -- \
docker run -i --rm -v "$PWD:/workspace" ghcr.io/gridhra/atx-mcp:0.6.7
Two things to keep in mind. `-i` is required: the server speaks the MCP stdio transport and needs stdin to stay open. And paths are container paths: the directory you bind-mount appears as /workspace inside the container, so import_asset and export_asset take paths like /workspace/photos/shot.jpg, not host paths.
The prebuilt native binary for your platform is pulled in automatically via optionalDependencies.
claude mcp add --scope user asset-transform -- npx -y atx-mcp --workspace /path/to/asset-workspace
Or add it directly to your MCP client config:
{
"mcpServers": { "asset-transform": { "command": "npx", "args": ["-y", "atx-mcp", "--workspace", "/path/to/asset-workspace"] } } }
--workspace (env: ATX_WORKSPACE) is the directory used as the asset store. It is created automatically if it doesn't exist.
--max-concurrent-tools (env: ATX_MAX_CONCURRENT_TOOLS) caps how many pixel-processing tool calls (import / inspect / detect_* / apply / preview / compare / mask) run at the same time; the default is the CPU count. Lower it on memory-constrained hosts. Tool work runs on dedicated threads, so the stdio transport (ping, cancellation, the vocabulary tools) stays responsive while images are being processed.
| Tool | Role | |||
|---|---|---|---|---|
list_operations | Compact catalog of the recipe vocabulary: every operation with a one-line description and terse parameter hints, plus the built-in preset names. Optional `category:"geometry"\ | "color"\ | "filter"\ | "output"` narrows it (read-only) |
explain_operation | Full reference for one operation: parameter table (type, range, required/default, semantics), ready-to-paste JSON examples and gotchas. A built-in preset name works too and returns its full operation list. An unknown name returns the valid operations and presets, grouped (read-only) | |||
import_asset | Import a local image into the workspace (sha256-idempotent). Takes path for one file or paths for a batch of up to 64 (a failing file does not abort the batch). Warns via already_derived_from when the bytes are already the output of a recipe in this workspace | |||
inspect_image | Inspect dimensions, EXIF summary, ICC profile, presence of GPS data, luma statistics, a sharpness score (variance of the Laplacian — relative, so compare it against a known-good capture of the same subject) and a perceptual_hash (dHash, 16 hex digits) for "is this the same picture?". include_exif:true additionally returns every EXIF field as {ifd, tag, value} entries — off by default because the full dump can carry GPS coordinates and names (read-only) | |||
detect_tilt | Estimate tilt angle via Canny+Hough (coarse) plus a projection profile (sub-0.1° refinement). Also returns horizontal/vertical family estimates; the full score curve is opt-in via include_score_curve:true. Returns "do not correct" when confidence is low (read-only) | |||
detect_document | Find the dominant quadrilateral (page, screen, whiteboard, sign) via Canny + contours and return it as a perspective-ready quad (tl, tr, br, bl) with confidence, area_ratio, an output_size_hint and a paste-ready suggested_operation. Returns quad:null with a reason (no_quad_found / already_rectified / low_confidence) rather than guessing (read-only) | |||
detect_text_blocks | Find the text-like blocks (headline, paragraphs, table, caption) via Otsu binarization + run-length smearing + connected components, in reading order, each with line_count, median_line_height_px and ink_ratio. legibility.line_height_at_1568_px says whether the text survives a downscale to long edge 1568 (below ~16px it usually does not), and legibility.recommended_bands splits the image into horizontal bands that clear that bar — each entry is already a crop operation to paste before render_preview (read-only) | |||
generate_mask | Generate a deterministic grayscale mask (linear_gradient / radial_gradient / luminosity_range / color_range) as a PNG revision with the same dimensions as the reference image, to be referenced from an operation's mask field (idempotent) | |||
render_preview | Apply a recipe (or a preset) at low resolution (long edge ≤768 by default, long_edge 256..1568 to hand a vision model a legible page) and return it as an inline image. `overlay:"grid"\ | "thirds"\ | "horizon" overlays composition guide lines, and overlay:"mask" (with mask_revision_id) tints the coverage of a mask (drawn on the preview only; it has no effect on the actual transform). Also reports estimated_vision_tokens, a rough width*height/750` budget for the returned image |
| apply_transform | Apply a recipe (or a preset) at full resolution and pr
Solo se muestra el principio; lee el resto en el repo